Authentication of an individual from a fingerprint is the process of comparing at least two instances of fingerprints (skin impressions) acquired by a fingerprint sensor to determine whether these impressions are likely to come from the same individual. Conventionally, fingerprints or a collection of fingerprint images are acquired from the same finger of the same individual during a so-called enrol process. This collection of fingerprint images is also denoted enrolled fingerprint images. The fingerprint images may be stored as images or typically as templates. A template is the container with the features extracted from the image(s) stored on a storage medium such as a hard-disk or solid-state drive.
Then, later on, when the individual wants to be authenticated, a fingerprint image is acquired and that fingerprint image, in the below also denoted a present image or verification image, is compared by advanced image processing to one or more of the enrolled images.
Due to the flexibility of the skin, no two fingerprints are ever exactly alike in every detail; even two impressions recorded immediately after each other from the same finger may be slightly different.
Authentication may comprise multiple steps; and the process thereof of deciding whether a fingerprint comes from the same individual is denoted verification. Another step of authentication is to decide whether a fingerprint image acquired by the fingerprint sensor comes from a live finger of a live individual or, alternatively, comes from an imitated or spoof finger or portion thereof in an attempt to gain unauthorized access. This step is sometimes referred to as liveness or liveness detection—the problem of finding a good method for deciding whether a fingerprint is live or spoof is also referred to as the liveness problem.
The terms imitated, spoof and fake are used interchangeably in the below. In any case an imitated or spoof finger refers to some means of leaving an imprint on the fingerprint sensor which may appear as a fingerprint, but however not being an imprint coming from a live finger touching the sensor.
In the below the term fingerprint should be construed as comprising a print from skin forming ridges and valleys such as from a human hand or a portion thereof e.g. the palm or from toes or sole of a human foot.
Conventionally, the liveness determination is performed prior to the verification process. Hence, only fingerprints deemed “live” are verified. In some cases a fingerprint is wrongly deemed “spoof” and thus not processed further. Accordingly, a non-robust liveness determination process will significantly degrade the overall quality of an authentication process based on fingerprints.
Structurally, a component for determining liveness is clearly separated from a verification component. That is, both of the components base their results on separate processing paths for the processing of the fingerprint image acquired by the fingerprint sensor.
In the article “Combining Match Scores with Liveness Values in a Fingerprint Verification System” by Marasco et al. it is investigated if combining liveness values with match scores can improve the verification performance in addition to improving the robustness to spoof attacks.
US 2007/0014443 (Atrua Technologies, Inc.) discloses a method for reducing the chances that real fingers will be falsely labelled as spoof. This is achieved by comparing data captured during verification to adjust the probability of a spoof. In an embodiment, the spoof detection is performed after fingerprint verification. Such an embodiment is said to be most useful during identification to avoid a time consuming database search.
EP2101282B1 (Fujitsu Ltd.) discloses a method wherein a matching determination threshold is set on the basis of the forgery similarity and the forgery difficulty together with the forgery determination threshold. Through the process, it is possible to reduce the possibility that the biologic object is erroneously determined as a spoof without increasing the risk in authentication with a fake. The matching determination threshold is a threshold used to determine whether a matching score between input matching data and registered matching data indicates sameness.